Textile-Sensing Wearable Systems for Continuous Motion Angle Estimation: A Systematic Review
R. Zhang, L. Chen, Yuanda Hu, Yueyao Zhang, Jiayi Chen, Tianzhan Liang, Xiaohua Sun, Qi Wang
Abstract
Textile sensors have demonstrated significant potential in next-generation wearable systems due to their excellent performance and unobtrusive nature. By building specialized sensing networks and algorithms, textile-based wearable systems can estimate the continuous motion angles of human joints with desirable accuracies. This article offers a systematic review aimed at identifying key challenges in this field and encouraging further applications of textile strain sensor networks within the human–computer interaction (HCI) community. To achieve this, we conducted an exhaustive literature search across four major databases: IEEE Xplore, PubMed, Scopus, and Web of Science, spanning from January 2016 to August 2023. Applying inclusion and exclusion criteria, we narrowed down 2684 results to a total of 24 relevant papers. To analyze these studies, we proposed a framework that incorporates both technical aspects – such as textile strain sensors, sensor placement, algorithms, and technical evaluations – and contextual factors like target users, wearability, and application scenarios. Our analysis uncovered two critical research gaps: First, it exists an incongruity between the development of textile-based wearables and the advancements in textile sensors. Second, there is a noticeable absence of contextual design considerations in this specific domain. To address these issues, we offer discussions and recommendations from three perspectives: 1) enhancing the robustness of textile-sensing networks, 2) improving wearability, and 3) expanding application scenarios.